Abstract
Embedded multicore processors running hard real-time applications such as engine control programs require an appropriate scheduling routine to meet the real-time deadline constraints. These applications typically consist of various conditional branches which change the flow of the program and the task executions based on sensors inputs and vehicle status information. Conventionally, dynamic on-line scheduling was the only option for such applications that have unpredictable runtime behaviors. However, techniques for compilers and schedulers allow static off-line scheduling to be applied to engine control programs by utilizing execution profile feedback methods to feed task execution time information to the compiler. This paper is the first to compare dynamic scheduling and static scheduling schemes through the OSCAR multi-grain automatic parallelizing compiler and its overheads on an actual engine control program using an embedded multicore processor implemented on an FPGA. Evaluations and analysis on the engine control program indicate promising results for static scheduling, recording a 2.53\(\times \) speedup on 4 cores compared to single core execution. In contrast, speedup on dynamic scheduling with 4 cores was only 0.86x compared to sequential execution. The evaluation shows that static scheduling with execution profile feedback methods is an effective tool for real hard-real time control applications that have task granularity that is too fine for dynamic scheduling on embedded multicore processors.
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The authors wish to thank Mr. Hirokazu Komori of Denso Corporation for his cooperation and support for the evaluation application.
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Oki, Y., Mikami, H., Nishida, H., Umeda, D., Kimura, K., Kasahara, H. (2021). Performance of Static and Dynamic Task Scheduling for Real-Time Engine Control System on Embedded Multicore Processor. In: Pande, S., Sarkar, V. (eds) Languages and Compilers for Parallel Computing. LCPC 2019. Lecture Notes in Computer Science(), vol 11998. Springer, Cham. https://doi.org/10.1007/978-3-030-72789-5_1
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